Geary's Irish Data

Description

This data set contains geographical informations about 25 counties of Ireland.

Usage

data(irishdata)

Format

irishdata is a list of 11 objects.

area

is a data frame with polygons for each of the 25 contiguous counties.

county.names

is a vector with the names of the 25 counties.

xy

is a data frame with the coordinates centers of the 25 counties.

tab

is a data frame with 25 rows (counties) and 12 variables.

contour

is a data frame with the global polygon of all the 25 counties.

link

is a matrix containing the common length between two counties from area.

area.utm

is a data frame with polygons for each of the 25 contiguous counties expressed in Universal Transverse Mercator (UTM) coordinates.

xy.utm

is a data frame with the UTM coordinates centers of the 25 counties.

link.utm

is a matrix containing the common length between two counties from area.utm.

tab.utm

is a data frame with the 25 counties (explicitly named) and 12 variables.

contour.utm

is a data frame with the global polygon of all the 25 counties expressed in UTM coordinates.

Source

Geary, R.C. (1954) The contiguity ratio and statistical mapping. The incorporated Statistician, 5, 3, 115–145.

Cliff, A.D. and Ord, J.K. (1973) Spatial autocorrelation, Pion, London. 1–178.

Examples

data(irishdata)

if(adegraphicsLoaded()) {

  if(requireNamespace("sp", quiet = TRUE)){
  g1 <- s.label(irishdata$xy.utm, Sp = irishdata$Spatial, pSp.col = "white", plot = FALSE)
  
  g21 <- s.label(irishdata$xy.utm, Sp = irishdata$Spatial, pSp.col = "white", plab.cex = 0, 
    ppoints.cex = 0, plot = FALSE)
  g22 <- s.label(irishdata$xy.utm, Sp = irishdata$Spatial.contour, pSp.col = "transparent", 
    plab.cex = 0, ppoints.cex = 0, pSp.lwd = 3, plot = FALSE)
  g2 <- superpose(g21, g22)   

  g3 <- s.corcircle(dudi.pca(irishdata$tab, scan = FALSE)$co, plot = FALSE)
  
  score <- dudi.pca(irishdata$tab, scan = FALSE, nf = 1)$li$Axis1
  names(score) <- row.names(irishdata$Spatial)
  
  obj <- sp::SpatialPolygonsDataFrame(Sr = irishdata$Spatial, data = as.data.frame(score))
  g4 <- s.Spatial(obj, plot = FALSE)
  
  G <- ADEgS(list(g1, g2, g3, g4), layout = c(2, 2))
  }
  
} else {
  par(mfrow = c(2,2))
  area.plot(irishdata$area, lab = irishdata$county.names, clab = 0.75)
  area.plot(irishdata$area)
  apply(irishdata$contour, 1, function(x) segments(x[1],x[2],x[3],x[4], 
      lwd = 3))
  s.corcircle(dudi.pca(irishdata$tab, scan = FALSE)$co)
  score <- dudi.pca(irishdata$tab, scan = FALSE, nf = 1)$li$Axis1
  names(score) <- row.names(irishdata$tab)
  area.plot(irishdata$area, score)
  par(mfrow = c(1,1))
}